Mental stress detection using bioradar respiratory signals

Stress detection techniques seek to provide an accurate assessment of mental health. This paper presents a new stress detection technique based on signals taken by a bioradar. The main advantage of this approach is its non-invasive nature since it uses a non-contact concealed mechanism that does not require the direct interaction between the person and the measuring device. In addition to being one of the first solutions based exclusively on respiratory signals, the novelty of the research also lies in the use of Recurrence Quantification Analysis (RQA) features on respiratory recordings. The RQA features, traditionally applied for heart rate measurements, allowed reaching a precision of 94,4% after the leave-one-subject-out-cross-validation using a multi-layer perceptron.